Method and system for monitoring rotor blades in combustion turbine engine

ABSTRACT

In accordance with one embodiment, a method for monitoring the health of blades in a combustion turbine engine is provided. Sensors mounted around the circumference of a rotor sense and record the passage of blades during turbine operation. Analysis of information from the sensors indicates whether a blade is damaged. Analysis of blade vibration and amplitude, as measured by the sensors, is used to predict the number of cycles the blade can undergo before replacement or maintenance.

BACKGROUND OF THE INVENTION

Turbine engines are used in many industrial applications in which amechanical driving force is needed to produce a useful result. One ofthe most visible applications is in the generation of electricity whereso-called “green” resources such as hydro-electric, wind turbine, orsolar photovoltaic power are not available. Even where such resourcesare available, they typically lack the flexibility to rapidly increaseor decrease the supply of electricity as demand fluctuates, whereasturbine engines do have such flexibility. Accordingly, although greenresources are becoming more prevalent, and may be expected to assume anever-increasing share of electrical power generation, it is anticipatedthat the use of turbine engines will continue into the indefinitefuture. That being so, there is a continuing need to continue toautomate, streamline, and increase the efficiency of systems in whichturbine power plays a significant role. One of the areas in whichautomation and efficiency may be enhanced is in the planning andscheduling of maintenance that may be due to causes other than normalwear and tear. Even new or newly refurbished turbine engines may havetheir life expectancies shortened by the incidence of unexpected damageto rotor or stator blades caused by the ingestion of foreign objects, orby latent manufacturing or assembly defects that become evident onlywhen the engine is being operated.

Embodiments of the present invention generally relate to rotor blades incombustion and steam turbine engines, both of which are extensively usedin the generation of electrical power, and more particularly to systemsand methods for monitoring the health of such blades. Rotor blades orrotating blades are used in many devices with several examples includingcompressors, turbines, and engines. A gas (or combustion) turbine enginetypically includes a compressor section, a combustor section, and aturbine section. The compressor and the turbine sections generallyinclude rows of blades that are axially stacked in stages. Each stageincludes a row of circumferentially-spaced stator blades, which arefixed, and a row of rotor blades, which are attached to and rotate witha central axis or shaft. In operation, the compressor rotor bladesrotate and, acting in concert with the stator blades, compress a flow ofair. The supply of compressed air then is used in the combustor tocombust a supply of fuel. The resulting flow of hot expanding gases fromthe combustion, i.e., the working fluid, is expanded through the turbinesection of the engine. The flow of working fluid through the turbineblades turns the central shaft that the turbine blades are attached toand that, in turn, causes the rotor blades to rotate. A steam turbineengine does not require a compressor section, as the transformation ofwater to steam provides the expanding gas necessary to rotate theturbine and provide torque to turn the shaft.

In either case, the energy contained in the fuel is converted into themechanical energy of the rotating shaft, which may be attached to thecoils of an electrical generator such that electrical power isgenerated. During operation of combustion turbine engines, because ofthe extreme temperatures of the hot-gas path, the velocity of theworking fluid, and the rotational velocity of the engine, compressorblades, which generally include both the rotating rotor blades and thefixed stator blades, become highly stressed with extreme mechanical andthermal loads. Steam turbine engines experience similar mechanical andthermal stresses to rotor blades in the turbine section of the engine.

Various factors adversely affect health of the rotor blades and lead tofatigue, stress, and ultimately cracking of the rotor blades. Theseinclude not only the mechanical and thermal loads mentioned earlier, butalso any damage that may occur when external objects or debris areinadvertently sucked into the compressor of an operating engine, orinternal components become dislodged. Such damage, frequently referredto as foreign object damage (“FOD”) or domestic object damage (“DOD”),can chip, bend, or weaken one or more rotor blades such that the bladeor blades will fail before their expected lifespan in the absence ofsuch damage. In some instances, blades may be affected in a manner thatcauses the tip of a blade to scrape or rub against the interior wall ofthe engine casing. Once a blade tip begins to rub, the blade may developcracks or other damage that can be used to predict failure. Bymonitoring the health of each blade in a turbine engine, unexpectedfailures may be avoided or substantially mitigated, and maintenance canbe scheduled to correct blade defects before a catastrophic failureoccurs.

Given the extreme conditions of operation for rotor blades, it isimportant for rotor blade health to be monitored closely. In many cases,blade failures may be predicted and avoided if data concerning bladedamage is accurately collected and monitored. Such data may includestrain levels and/or crack formation/propagation in certain highlystressed areas on the blade. Blade health monitoring is typically doneusing sensors embedded in the casing of a turbine engine that preciselymeasure the passage of the tip of a rotating blade. By using a pluralityof sensors placed at precise locations around the circumference of arotor stage, vibrational characteristics of each blade can be measured,recorded, and analyzed, and determinations made about the health of eachblade.

It is well understood that blades in an operating turbine have resonantvibration frequencies that depend on a number of parameters, includingthe characteristics of the blade material, blade size, rotational speed,and a variety of other factors. In this context, the term “resonantvibration frequency” refers to the vibration frequency of a blade underoperational conditions, and does not refer to the rotational frequencyof the shaft to which the blade is attached. Resonant vibrationfrequencies of blades in an undamaged engine can be determinedempirically and monitored during start-up, shut-down, and normaloperation. A change in the resonant frequencies of a blade is usuallyindicative of damage to the blade, and such frequency variations may beregarded as warning flags that a blade's health may be deteriorating.Once a blade develops a crack, changes in the resonant frequencies ofthe blade can be used to track the progression of the crack. As a crackgrows in length, the time to blade failure will decrease, andpredictions regarding remaining blade life may be made, based upon therate of growth of the crack. Thus, with adequate monitoring and the useof algorithms to analyze blade vibration data, a blade's life expectancemay be estimated, and appropriate steps be taken to replace the bladewithout adversely impacting other system operations.

SUMMARY OF THE INVENTION

The following presents a simplified summary of the invention in order toprovide a basic understanding of some aspects of the invention. Thissummary is not an extensive overview of the invention. It is intended toneither identify key or critical elements of the invention nor delineatethe scope of the invention. Its sole purpose is to present some conceptsof the invention in a simplified form as a prelude to the more detaileddescription that is presented later.

In an overview of the invention, the system detects blades vibrating atabnormal resonant frequencies caused by secondary damage by detectingthe event. The events are detected by any of several methods, dependingupon the cause of the damage. In the event that damage is caused by ablade rubbing against the engine casing, the blade vibrations willresonate erratically for a short period after the event. The system willpick up the erratic signature and the algorithm will then begin tocalculate the remaining life of the blade. In the event of a crack, orof corrosion or FOD/DOD damage, the blade will develop a differentvibration signature which will cause a permanent change in thefrequency. The permanent change will trigger the algorithms to begin acalculation to predict useful remaining blade life. Once the algorithmsare triggered the system counts and records the number of times theblade vibrates at a peak resonance frequency during thestartup-run-shutdown cycle. Blade replacement recommendations aredetermined by the number of times a blade is detected vibrating at apeak resonant frequency plotted on a normalized Goodman diagram for thetype of damage or by the number of times it is detected vibrating at aresonant frequency that shows differences to its predicted baselinenatural resonant frequency response. As the number of peak vibrationepisodes increases, the need for replacing the blade becomes greater. Anempirical model using Finite Element Model results combined withhistorical experience provides a reference for determining when a bladehas experienced enough peak amplitudes that replacing it is indicated.If damage should occur while the turbine is in steady state runningcondition, it will be manifested by the presence of peak amplitudes thatwere not present at an earlier time.

In accordance with one embodiment, a system and method for monitoringblade health in a turbine engine is provided. The system for monitoringblade health includes a plurality of sensors to collect data from whichblade vibration frequency, and resonant blade frequencies, may bedetermined. Although any instrumentation system that precisely monitorsand records blade passage times may be used to monitor blade health, inan exemplary embodiment, the system may use an arrival time analysis(“ATA”) health monitoring instrumentation system such as that providedby Agilis Engineering, Inc., to provide precise data regarding thepassage of rotor blade tips, or parts of rotor blade tips (e.g., leadingedge, midpoint, or trailing edge) proximate to one or more sensorsmounted within the engine casing. Because of the extreme heat generatedin the turbine section of a combustion turbine engine, sensors for suchengines will normally be mounted within the compressor section, and willmonitor the health of rotor blades in the compressor. In steam turbineengines, which do not require compressors and which typically operate atlower temperatures, sensors may be mounted in the turbine section wherethe health of rotor blades in the turbine can be monitored.

ATA system sensors, which may be eddy current sensors, proximitysensors, or any other suitable sensor, and associated instrumentationcan sense the passage of each blade and store data related to therelative positions of parts of a blade without coming into directcontact with any blade. Blade arrival data is collected for each bladefrom an undamaged engine and is stored for later retrieval and analysis.Precise arrival times may be recorded for various parts of a blade, suchas leading edge, midpoint, trailing edge, or the like. If a bladethereafter incurs twisting or torsional damage that changes its shape ororientation, analysis of historical data prior to the onset of damageand comparison with recent data collected after damage was incurred, mayindicate changes in the blade's shape or orientation resulting fromdamage, or may reveal changes in a blade's vibration frequency which maybe indicative of the presence or propagation of cracks in the blade.Data extracted from the system may be further processed to provide anindication of remaining blade life.

The system may include a processing module to process the blade healthdata and to store the analysis data on a non-transitory computerreadable medium. The system may be configured to use the stored analysisdata to schedule shutdown of the engine. Optionally, the system may alsocheck inventory for parts needing repair or, when the parts are notavailable may automatically place orders for the non-available parts. Inan embodiment of the subject matter disclosed herein, the system mayschedule hardware inspection during normal shutdown of the engine, andblade repair specialists for inspection of the blade. The system mayalso catalog every action for future references to data and actionsperformed by the system. In yet another embodiment, the system may beconfigured to allow manual correction, overwriting, or editing of anyaction.

One attribute of the invention is that real-time measurements areprocessed using multiple algorithms and logic to consider differentblade health indicators simultaneously. The multifaceted processingapproach is intended to provide redundancy in the detection andpredictive capabilities of the invention. Feedback on predictiveanalytics is available through direct blade measurement such asfrequency trending. Such redundancy minimizes operation risks throughdirect response trending while offering predictive capabilities formaintenance and unit operation planning.

The invention relies on processed data acquired by the ATA engineinstrumentation system. This data includes:

-   -   Vibration frequencies for each blade being monitored    -   The amplitude of vibrations at resonant frequencies    -   Number of cycles (start-up/shut-down) for each blade    -   Tip positions (leading edge, middle, trailing edge) of each        blade    -   Radial clearances for each blade

These files are frequently updated to the system's database depending onthe blade response and vibration amplitude threshold levels set withinthe ATA system. From this data, blade monitoring algorithms can beapplied to determine:

-   -   Frequency trending    -   Clearance monitoring    -   Position trending    -   Damage tolerance    -   Damage accumulation

In addition to the processed ATA instrumentation system data, a numberof static input files are also used in the invention. These filesinclude:

-   -   Stress input files from ANSYS finite element analyses    -   Material allowables    -   Calibration constants used to relate measured deflections and        stress predictions    -   Surface condition assumption inputs    -   Blade revision control settings

These files are considered static (unchanging) except as needed tocalibrate calculations and to account for physical changes made to therotor blades (repairs, replacement, etc.). For example, capability isprovided to account for unique blades within the system so long as thestress input files are updated with the corresponding analysis results.Static files may be created from data collected from the turbine enginebeing monitored at a time when it was in a new and undamaged state, orthey may include empirical historical data collected from similarengines operating under similar circumstances. In this manner, thecollective experience of operators of the same model turbine engines maybe pooled and used to establish predictive damage models for variouskinds of damage events.

Once the static input files are installed, the system can operate on theincoming ATA system data. Calculations are performed within the system'sdatabase to evaluate blade life consumption (fatigue life) and crackpropagation (fracture mechanics) based on measured blade responses.Frequency and relative position shift information is also imported fromthe ATA system and stored in the system's database. Calculated summaryresults are provided, along with select historical data for display andfor alerts within the system. Additionally, a graphical user interface(GUI) is provided to allow the turbine engineers and operators access todetailed historical information, projections, and trend data.

While the resonant vibration frequency of a damaged blade may be sensedand known, it is not normally the primary parameter used in thecalculation of useful life of the blade before replacement. Rather, itis the number of times (i.e., cycles), and the duration of time, thatthe blade vibrates at its resonant frequency that determines blade lifeand the need for replacement.

The system of this invention uses existing hardware instrumentation andfinite element model algorithms to provide data from which the remaininglife of cracked or damaged rotor blades may be predicted. The system isbased upon the detection of the onset of a crack or damaged blade. Oncea damage location is detected the algorithms are applied to determinethe remaining life of the blade. Information used for blade healthanalysis can be considered in any of five general categories, explainedbelow.

Frequency trending is the monitoring and recording of blade resonantfrequency variations. As the resonant frequency of a blade changes, theamount and rate of frequency change can be used to determine the lengthand rate of growth of a crack in the blade. When cross-referenced withempirical data, which may include the number of cycles, an approximationof when the blade will critically fail may be made.

Clearance monitoring is the tracking and monitoring of blade clearanceswithin the engine casing. Baseline radial clearances are recorded andclearances are monitored for occurrences of tip rubs. Blade tip rubshave been shown to adversely affect the blade tip durability, and may beindicative of other damage to a blade. Blade tip rubs should beinspected and analyzed to assess whether the rubs are of sufficientseverity to initiate cracks in the blade.

Position trending monitors and records any deviation in the relativeposition of a blade with reference to other blades in a stage. Baselinetip positions are recorded when the engine is undamaged, and deviationsin blade position are noted. A change in blade position suggestspermanent blade distortion which may have been caused by foreign ordomestic object damage or the initiation of a crack in the blade. Themagnitude and trend of the distortion will indicate the kind andimmediacy of response that is appropriate for the condition. Positiontrending also detects other changes in a blade, such as the relativepositions of the blade leading edge, middle section, or trailing edge atvarious sensing points about the circumference of the casing. Suchinformation may be used to determine torsion or twisting of a blade, oroscillations (flutter) during a blade's rotation about the central shaftof the engine.

Damage tolerance is determined by the vibration amplitude and the numberof vibration cycles a damaged blade may experience. Turbine engines usedto generate electricity typically operate at a constant speed, and varyfrom that speed only during startup or shutdown. Vibration cycles arerelated to engine startup and shutdown, and during the course of astartup or shutdown, a blade may experience a number of resonantvibration frequencies, which are usually indicated bygreater-than-normal vibration amplitudes. Both the amplitude of bladevibrations and the number of cycles the blade experiences are factorsthat may affect expected blade life. Stress intensities are calculatedfrom this information and are used to determine crack growth resultingfrom each vibration cycle and amplitude. Corrective action time isprojected from crack growth rates and prediction of critical cracklength.

Damage accumulation provides the existing state of fatigue damage to ablade resulting from vibration. Vibration amplitude and the number ofvibration cycles are measured for all responding modes, and damage dueto vibration is summed over time. Corrective action time is projectedfrom damage accumulation rates.

It is therefore a purpose of the invention to detect changes in resonantblade frequencies and monitor such changes over time to predictremaining blade life.

It is another purpose of the invention to detect changes in relativeblade position with respect to a previous position of a blade or withrespect to other blades, or both, and to determine whether a blade hasbeen twisted or bent or has otherwise had its position changed from anearlier measurement.

It is a further purpose of the invention to monitor blade tip clearancesor blade tip rubs against an engine casing to determine actual orpredicted damage to a blade and to schedule timely maintenance prior toblade failure.

It is another purpose of the invention to determine the damage toleranceof one or more blades in a turbine engine to permit diagnosis andanalysis of the health of the engine.

It is yet another purpose of the invention to monitor the accumulationof damage to one or more blades and in a turbine engine to predictremaining time or cycles of operation before corrective action isrequired.

These and other purposes of the invention are more fully explained inthe description of preferred embodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagrammatic depiction of one embodiment of the overallsystem and major components.

FIG. 2 shows an exemplary frequency trending analysis graph such as maybe used in accordance with one embodiment of the invention.

In accordance with one embodiment of the invention, FIGS. 3a and 3b showexemplary clearance monitoring graphs from which two failure modes maybe determined.

In accordance with one embodiment of the invention, FIGS. 4a and 4b showexemplary position trending graphs from which two types of blade damagemay be detected.

FIG. 5 depicts an exemplary Campbell Diagram on which resonantfrequencies may be shown for different engine orders in accordance withone embodiment of the invention.

FIG. 6 is a graphical depiction in accordance with one embodiment of theinvention, showing the movement of data through the system.

FIG. 7 is a flow chart in accordance with one embodiment of theinvention, showing the process of detecting, identifying, and actingupon information relating to blade health.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 depicts the overall system of the invention 10 and the majorcomponents within it. A turbine engine 12 is fitted with sensors thatprovide arrival time analysis (“ATA”) health monitoring instrumentationdata 14 needed to enable the system to be analyzed.

The ATA system 14 is a non-intrusive stress measurement hardware systemthat includes a set of probes mounted within the turbine casing for eachrotor stage. In a preferred embodiment, eight (8) case mounted probesper stage accurately determine the arrival time of a blade tip at aparticular case location. Optical, capacitive and eddy current probesmay be used for the arrival time measurement. The probes are placed atunequal, pre-determined distances around the case to record the time ofan arriving blade tip, and to track its progress during a rotation. Theplacement of the probes is dependent upon a number of factors, such asthe length and stiffness of turbine blades, and can be determined from acalculation designed to optimize the observation of specific engineparameters.

The arrival time of a blade may be determined by “taking a picture”—thatis, recording the outputs from all sensors—for example, every 2nanoseconds. As the blade approaches a sensor, a part of the blade edgecatches the edge of the picture “frame,” and the time that that occursis recorded. The strength (amplitude) of the returning signal determineshow much of the blade is being “seen.” Assuming that 8 pictures aretaken between the time the blade tip first enters into the viewing frameand the time the entire blade is under the frame, and that theamplitudes and times of the 8 pictures taken over the course of a bladeencounter are recorded, a curve or line may be fitted to the points. An“event” can be defined as the point of maximum amplitude change, and thecorresponding time that this occurred. This method provides highlyaccurate event descriptions and allows responses to be seen on the sub-1mil scale. The blade may be said to “arrive” at the point of maximumamplitude change, and the corresponding time that this occurred.

The arrival times of each blade (also known as “tip timing”) areconverted to blade positions relative to Once Per Revolution (OPR), or“center time” by using the rotational velocity and the radius of themeasurements. In the analysis portion, each blade's position is thencompared to a precisely calculated “undeflected blade position,” toyield a deflection value for each blade. Sensors determine variances inblade passing times and, when taken at multiple points around thecasing, enable an analysis of the frequency and amplitude of thevibrations of a blade.

Tip timing, has many capabilities for detection and monitoring of thepropagation of blade cracks in turbo machinery. These analysiscapabilities include monitoring static blade characteristics such asblade untwist as well as monitoring vibration characteristic such asresonant amplitude, frequency and damping. Trending of these static andvibratory characteristics can be used to detect and monitor propagationof developing cracks in the turbine blades.

In blade tip timing, the center-time for all blades passing a probe iscalculated using the arrival times of all the blades and averaging themover 3 revolutions. The time difference between the center time and theactual arrival time for mid-blade edge of a particular blade, asmeasured by a probe, represents the difference between when the bladeshould pass and when it actually does.

Data from multiple probes at a common axial location are used todetermine the mode frequency of a vibration. Once fit, amplitude andphase data can be calculated along with engine order, peak response rpm,data fit, absolute phase, damping, and other vibratory characteristics.Probes are placed in specific locations around the case of the givenapplication to optimize on certain (pre-specified) engine orders. Inthis manner, the locations of the probes on the case allow for moreaccurate data in the regions where resonances are bound to occur.

The deflection measurement is a peak-to-peak measurement derived fromthe axial and tangential deflections of the rotor blade. The shape ofthe modes in interest, as well as the probe's axial position on theblade (leading edge, mid blade, trailing edge), determine thesensitivity the system will have to a particular mode.

It is understood that the presence of a crack alters the operatingvibration frequency of a blade and, thus, may be used to warn of acompromised blade. As crack length grows, the blade's vibrationfrequency will change, making it possible to monitor crack length bymonitoring blade vibration frequency. When multiple sensors are used,blade vibration frequency can be determined with precision by notingdifferences, throughout a given rotation cycle, in the relativepositions of a blade tip or edge, and a midpoint or leading edge. Suchinformation, coupled with differences in the expected passage time of ablade and actual passage time, can be used to determine a blade'svibration mode and resonant frequencies both before the onset of damage,and during the progression of damage which may be a function of cracklength. However, in order for blade health to be monitored, and bladelife expectancy to be determined, raw data regarding blade vibrationmodes and resonant frequencies must be analyzed and processed.

Rotor speed for a turbines powering electrical generators in the UnitedStates is typically 3600 rpm except during periods of startup andshutdown, although other steady-state shaft speeds are used in othercountries, and, through the use of gearboxes, other steady state shaftspeeds may be used where efficiency or design so require. Thissteady-state shaft speed relates only to the turning of the rotor, andis not to be confused with the vibration frequency of a blade, which isprimarily dependent upon factors inherent to the blade and itsmanufacture. It is the vibration of the blade that is important indetermining the predicted life of a rotor blade before replacement.

In an embodiment of the invention, “normal” vibration frequency ofblades on a rotor turning at a steady-state shaft speed (for example,3600 rpm) is sensed and recorded. A blade that has suffered damage willresonate at a different frequency than an undamaged blade. Blades havingabnormal resonant frequencies when compared to baseline undamaged bladefrequency may be assumed to have some damage. The onset of damage willcause a rapid shift in frequency and will continue to change if thedamage and/or crack grows.

As rotor speed is increased during startup from 0 to 1200 rpm to 2400rpm to 3600 rpm, blade vibration frequency is sensed and recorded. Atcertain rotor rotation speeds during startup and shutdown, blades willdemonstrate natural resonant frequency peaks. The amplitude of bladevibrations at such resonant frequencies is greater than the amplitude ofblade vibrations at other rotation speeds, and can be detected andmeasured. As rotation speed increases, blade vibration frequenciesremain within a defined range, but reach peak amplitudes outside of thatrange at resonant frequencies which occur at certain rotation speedsduring startup and shutdown. Peak amplitudes of blade resonantfrequencies can be used to calculate stress intensities and to determinethe growth of a crack resulting from each vibration cycle at thatamplitude. Resonant blade frequencies can cause blade damage, and thetime spent at such resonant frequencies should be minimized if possible.

The resonant frequencies of a blade will change if the blade shouldbecome damaged. Damage is typically caused by foreign objectsinadvertently entering the engine (“FOD”) or internal componentsbecoming dislodged (“DOD”), by blades rubbing against the case, and bycorrosion. The amount of change in resonant frequency will differsomewhat, depending upon the amount of damage to the blade. Damagedblades are typically identifiable by a difference in amplitudes whichset them apart from the vibration frequencies of “normal” undamagedblades. In addition, the onset of damage can be captured by suddendifferences in the blade frequency and amplitude.

In FIG. 1, ATA system data 14 includes at least blade resonancefrequencies 16 (“HCF” or high cycle fatigue data); instrumentationsystem summary data 18; resonant frequency shift data 20; and staticposition data 22. Blade resonance frequencies 16 are useful fordetermining cycle life projections. At 24, the ATA system data 14 isread into a system database 26 in real time. The system database 26 alsomaintains tables of additional data in the form of program static inputfiles 30.

Static input files 30 include at least stress input files from finiteelement analyses 32, material Goodman allowables in the form ofpolynomials coefficients 34, calibration constants used to relatemeasured deflections and stress predictions 36, blade revision controlsetting files 38, and surface condition assumption inputs 40. Thesefiles are combined with an initialization file 42, and the combinedinformation is passed to a program 44 that reads the information intothe database 26. A module 28 accessible to the database 26 may providefurther processing of information in the database as well as processingATA system data being read into the database 24. Processing module 28also processes data from the database 26 being written to proceduralinput universal files 52 or for passage to procedural input module 54.Static input files 30 are essentially unchanged except as needed tocalibrate calculations and to account for physical changes made toindividual compressor blades. In order to accomplish this, stress inputfiles must be updated with the corresponding analysis results whenever ablade analysis is conducted.

At 28, a sequence of calculations is made on the data to determineGoodman and finite materials information. This information may then beretained in the database 26 where it is available via a GUI 50 toengineers 46 who may use historical information and trend data to makeprojections regarding the system or to gain operational insight tominimize risk and increase blade life. In addition, selected calculateddata may be sent to a procedural input (PI) module 54 where it may beused for outage planning and scheduling.

FIG. 2 is a graph showing an exemplary relationship between a blade'svibration frequency and the length of time or number of start and stopcycles the blade undergoes. Tip timing is a method of measuring bladevibration frequency. Through the proper placement of sensors in aturbine engine's casing, a blade's actual arrival time may be preciselydetermined and compared to its anticipated arrival time. From thisinformation taken at a number of locations around the circumference ofthe casing, the frequency of vibration of individual blades can bedetermined. As shown in FIG. 2, at 60, the blade has not been damagedand vibrates at a constant baseline frequency during operation of theturbine. During this time, the engine may undergo a number of start-stopcycles, and during each such cycle, the blade will exhibit resonantfrequencies at various rotational speeds. However, in environments suchas the generation of electrical power, where the engine operates at aconstant speed other than during a start-stop cycle, the blade'sresonant frequencies will not coincide with the engine's constantrotational speed and will be seen on sensors as having greateramplitudes only during a start-stop cycle. As long as there is no damageto the blade, such operational frequency characteristics may continueindefinitely. If a blade should suffer damage, either because ofexternal factors or through normal stresses, the blade's vibrationfrequency will change. In FIG. 2, damage to the blade has occurred at 62and thereafter the blade's vibrational frequency begins to decline. Oncethis occurrence is noted, the blade may be subjected to heightenedscrutiny and monitoring, and the propagation and length of the crack maybe followed as the blade frequency declines, as at 64. Using a frequencytrending algorithm, the expected remaining blade life may be calculatedin number of cycles or in time, depending upon the operatingenvironment, and decisions regarding replacement or maintenance may bepredicated upon such calculations. A minimum allowable frequency may beempirically determined, and when a blade's vibrational frequency reachesthat threshold 66, corrective action must be taken. In the absence ofcorrective action, total failure of the blade may occur at any point 68,and predictions of the time or number of cycles remaining before totalfailure will become increasingly hazardous.

FIG. 3a depicts one form of blade clearance monitoring and analysis.Sensors installed in the casing will have determined a baseline radialclearance for each blade 70. If a blade has been slightly damaged, thatfact may be evidenced by a gradual narrowing of the tip clearance 72between the blade and the engine casing. If the narrowing occurs asdepicted in FIG. 3a , actual contact between the blade tip and thecasing (“blade tip rub”) may be predicted, and maintenance can bepreplanned. In an exemplary embodiment, sensors monitor clearances foroccurrences of tip rubs 74. Tip rubs may adversely affect blade tipdurability. Thus, monitoring the occurrences of tip rubs may helpdiagnose tip durability. The sensor data may be used alone or togetherwith frequency trending or position trending data to diagnose andpotentially schedule a technician to remove crack initiators caused bythe tip rubs. Further, the system may store the effects of tip rubdamage for future calculation and predictions.

FIG. 3b depicts blade clearance monitoring in which blade damage occurssuddenly 76, resulting in immediate rubbing of the blade against thecasing. In this case, depending upon the severity of the tip rub, it maybe necessary to immediately shut down the engine. Where emergencyshutdown is not indicated, however, a review of frequency trending andposition trending data can provide an analysis of the severity of thetip rub and possible crack formation, and will indicate the need forimmediate or longer term maintenance.

A graph of position trending is shown in FIGS. 4a and 4b . Positiontrending tracks the variation in position of a blade while it isrotating, and provides information regarding potential damage to theblade. Position trending is highly useful when analyzed in conjunctionwith frequency trending, as a variation from a baseline in both positiontrending and frequency trending can provide information regarding theamount of twisting of the blade as contrasted with the length of a crackthat may be in the blade. When this information is known, informeddecisions can be made regarding the kind and severity of damage to ablade, and life expectancies may be based thereon.

As shown in FIG. 4a , where position trending shows that a blade'sposition is changing constantly over time from an initial position 80 toa series of intermediate positions 82, there may be continuing damagethat will lead to a critical failure 84. In this case, cross-referenceto frequency trending (as depicted in FIG. 2) may reveal that a crack ispropagating (as would be expected if frequency is trending downward),and a non-scheduled maintenance shutdown to inspect and correct thecondition may be required. Conversely, as is depicted in FIG. 4b , if ablade's position changes suddenly 86, but thereafter remains constant, across-reference to frequency trending may indicate that there are nocracks (as would be expected if there is no downward trend infrequency), or that any existing cracks are not propagating. In thiscase, it may be discovered that the blade has undergone non-criticaldistortion, and that damage is not progressing. In this case, the blademay be expected to perform satisfactorily until the next scheduledmaintenance.

FIG. 5 depicts a representative Campbell Diagram which is used inanalyzing damage tolerance. In FIG. 5, resonant blade frequencies in Hzare shown as horizontal lines intersecting the Y-axis as engine drivers.Modes 1 and 2 (90, 92) represent different ways (modes) in which a blademay be distorted (twisted, bent, flexed, etc.) at a particular resonantfrequency. Vertical lines 94, 96 represent turbine speed in revolutionsper minute (RPM) (shown on the X-axis), and indicate exemplary speeds atwhich the turbine engine may momentarily operate at a constant speedduring startup or shutdown 94 or may run continuously during normaloperation 96. If resonant frequencies should coincide with thoseconstant engine speeds, damage to the blades may occur. Radial linesemanating from the origin represent engine orders—that is, resonantfrequency responses that occur at various harmonics of engine RPM wheren=½, 1, 2, 3, 4, etc. Blade damage may be expected to accumulate whenthe engine drivers on the Y-axis intersect the rotor RPM (X-axis) at aunique engine order or within a percentage margin. On the embodimentshown in FIG. 5, circle 99 indicates such an intersection of enginedriver 90 with the engine's normal operational speed 96, and isconsidered to be a “keep out” zone during engine operation. If an engineorder radial should intersect with an engine driver at a constantoperational speed, such as at “keep out” zone 99, blade vibrationfrequencies would reach local peak amplitudes and add to theaccumulation of damage to a blade. During startup and shutdown, as theengine speed necessarily passes through these frequencies, damageaccumulation will occur to a greater or lesser extent, depending on howlong the unit idles at those points.

In FIG. 5, engine orders N=1 and N=2 intersect with normal operationalspeed line 96 near engine driver 90 for mode 1. A margin box 98 extendsin the horizontal (engine RPM) and vertical (blade vibration frequency)directions by an amount of 10% of the X and Y values. As depicted,engine orders N=1 and N=2 pass below “keep out” zone 99, and are notclose enough to cause damage to a blade to accumulate under thoseoperating conditions.

FIG. 5 is normally created from actual data obtained from an operatingturbine engine. The data are used to measure vibration amplitude andnumber of vibration cycles for all responding modes, and to calculatestress intensities to determine crack growth resulting from eachvibration cycle and amplitude. An algorithm for damage accumulationmeasures and records vibration amplitude and number of vibration cyclesfor all responding modes. Vibration stresses are calculated and are usedto determine fatigue damage resulting from each vibration cycle andamplitude. Damage due to vibration is summed over time and correctiveaction time is projected from the measured rates of damage accumulation.In addition, incremental crack propagation is summed over time andcorrective action may be projected from crack growth rates andprediction of critical crack length. In this manner, the damagetolerance of a blade can be determined, and decisions made regardingmaintenance or replacement.

FIG. 6 provides a graphic representation of the system of this inventionin accordance with one embodiment. The system comprises sensors 100 thatgather ATA information in real time and provide it to ATA systemprocesses that enter relevant parameters into the database 26. ATAsystem processes include determinations of blade vibration frequency102, resonant response amplitudes 104, number of startup and shutdowncycles 106, blade tip positions 108, and blade tip radial clearances110. Historical data 112 is provided, and the information is sent to aprocessing module 114 where the algorithms are applied to determinefrequency trending 116, clearance monitoring 118, position trending 120,damage tolerance 122, and damage accumulation 124. Results of theseanalyses are then provided to other systems 126 for monitoring and anynecessary actions.

FIG. 7 is a flow chart of an embodiment showing how identified anomaliesin blade health may be processed. At 130, data from sensors is receivedand compared with historical data to determine whether real-timeinformation is within historical limits. For example, data may beprovided from proximity sensors 132, from eddy current sensors 134, andfrom stored historical data 112. While proximity and eddy currentsensors are specifically noted, it is possible that other kinds ofsensors may exist or may be developed that will provide blade position,shape, frequency, and clearance information, and such sensors andinformation would fall within the scope of the invention. Anomaliesidentified at 130 are then sent to a processing unit 138 to determinethe severity of the anomaly, based on a further analysis of the data.Actions may be taken based on the analysis. At 140, if a criticalfailure is indicated, an emergency shutdown of the engine 142 may beinstructed. Normally, an emergency shutdown will be automated, withouthuman intervention, and would be done in circumstances where the engineis subject to imminent failure and would be expected to self-destruct ifimmediate shutdown is not done. If the anomaly is not a criticalfailure, the system then checks for the presence of a critical condition144. If a critical condition is detected, a critical warning is sent tothe operator 146, but further action may depend upon human interventionby the operator. In the event that the anomaly is of an unexpected, butnot critical, condition 148, the system may modify the maintenanceschedule 150 for the engine to have the unexpected condition reviewed orcorrected at a time when the engine can be shut down without causing adisruption of the system. If the anomaly is abnormal but otherwisewithin acceptable limits 152, no action is taken. In all cases, both theanomaly and any consequent actions are recorded back into the databaseas historical data 154.

In some embodiments, when anomalies are detected, the system may alsocheck inventory for turbine parts needing repair or when the parts arenot available may automatically place orders for the non-availableparts. In an embodiment of the subject matter disclosed herein, thesystem may schedule hardware inspection and blade repair specialists forinspection of the damaged rotor blade. The system may also catalog everyaction for future references to data and actions performed by thesystem. In yet another embodiment, the system may be configured to allowmanual correction, overwriting, or editing of any action.

It is to be understood that the above description is intended to beillustrative, and not restrictive. For example, the above-describedembodiments (and/or aspects thereof) may be used in combination witheach other. In addition, many modifications may be made to adapt aparticular situation or material to the teachings of the inventionwithout departing from its scope. While aspects of the inventiondescribed herein are intended to define the parameters of the invention,they are by no means limiting and are exemplary embodiments. Many otherembodiments will be apparent to those of skill in the art upon reviewingthe above description. The scope of the invention should, therefore, bedetermined with reference to the appended claims, along with the fullscope of equivalents to which such claims are entitled. In the appendedclaims, the terms “including” and “in which” are used as theplain-English equivalents of the respective terms “comprising” and“wherein.” Moreover, in the following claims, the terms “first,”“second,” and “third,” etc. are used merely as labels, and are notintended to impose numerical requirements on their objects. Further, thelimitations of the following claims are not written inmeans—plus-function format and are not intended to be interpreted basedon 35 U.S.C. §112, sixth paragraph, unless and until such claimlimitations expressly use the phrase “means for” followed by a statementof function void of further structure.

This written description uses examples to disclose the variousembodiments of the invention, including the best mode, and also toenable any person skilled in the art to practice the various embodimentsof the invention, including making and using any devices or systems andperforming any incorporated methods. The patentable scope of the variousembodiments of the invention is defined by the claims, and may includeother examples that occur to those skilled in the art. Such otherexamples are intended to be within the scope of the claims if theexamples have structural elements that do not differ from the literallanguage of the claims, or if the examples include equivalent structuralelements with insubstantial differences from the literal languages ofthe claims.

What is claimed is:
 1. A method of monitoring rotor blades in anoperating turbine combustion engine comprising the steps of: positioninga plurality of sensors around a plurality of rotor blades in a stage ofa combustion turbine engine; collecting and storing information in amemory regarding the relative position of each blade in said pluralityof rotor blades when said rotor blades are in an undamaged condition;said sensors detecting and transmitting to a processor the times ofpassage of one or more of said rotor blades in said stage duringoperation of the turbine combustion engine; determining the physicalcondition and orientation of said one or more rotor blades by comparingthe anticipated arrival times of one or more blades with actual arrivaltime information transmitted from said plurality of sensors; analyzingsaid information transmitted from said plurality of sensors to identifyand count the cycles in which each of said one or more rotor bladesexperiences resonant frequencies; recording and storing in a memory thenumber of cycles and the frequencies and amplitudes of vibration foreach resonant frequency; comparing recent information with historicalinformation to develop a prediction, based upon the frequencies and peakamplitudes of vibration of the number of cycles said one or more rotorblades may be expected to experience before failure; using saidprediction to schedule events relating to said turbine engine, saidevents including at least scheduled maintenance.
 2. The method of claim1, wherein said plurality of sensors includes eddy current sensors andproximity sensors.
 3. The method of claim 1 wherein said step ofdetermining the physical condition and orientation of said one or morerotor blades further comprises the steps of determining and recording anexpected arrival time for different parts of a blade whose physicalcondition and orientation are being determined, and comparing saidexpected arrival times with actual arrival times for each of said partsof said blade.
 4. The method of claim 2 further comprising the steps ofpositioning said sensors within a casing surrounding said blades andanalyzing information from said proximity sensors to monitor theclearance between a blade and said casing for one or more of saidblades.
 5. The method of claim 3 wherein the step of positioning aplurality of sensors around a plurality of rotor blades in a stage of acombustion turbine engine further comprises positioning said sensorsaround the circumference of said blades' path of rotation such thatexpected and actual arrival times for parts of each blade can beanalyzed to identify deformations in the shape of each blade and todetermine the frequency of vibration of each blade during the operationof said combustion turbine engine.
 6. The method of claim 5 furthercomprising analyzing said blade vibration frequencies to determinefrequency trending for one or more of said blades.
 7. The method ofclaim 6 further comprising analyzing blade vibration frequencies andblade actual and anticipated arrival times to determine positiontrending for one or more of said blades.
 8. The method of claim 7further comprising analyzing blade damage to determine damageaccumulation to one or more blades.
 9. The method of claim 8, whereinsaid prediction of the number of cycles each said blade in a firstcombustion turbine engine may be expected to perform before failure isbased upon empirically collected data related to the performance ofblades in other combustion turbine engines of the same model as saidfirst combustion turbine engine, and in which blade damage is similar tothe damage to blades in said first combustion turbine engine.
 10. Themethod claimed in claim 8, further comprising determining expected bladelife by analyzing damage accumulation for each cycle and determining apredicted blade failure if said damage accumulation continues at thesame rate.
 11. The method claimed in claim 10 wherein informationregarding damage to one or more blades is stored in a database and madeaccessible for analyses to be performed in the future.
 12. A system formonitoring rotor blades in an operating turbine combustion engine, saidsystem comprising: a plurality of sensors positioned around a pluralityof rotor blades in a stage of a combustion turbine engine; a memorycollecting and storing information regarding the relative position ofeach blade in said plurality of rotor blades when said rotor blades arein an undamaged condition; a processor receiving information transmittedfrom said plurality of sensors indicative of times of passage of one ormore of said rotor blades in said stage during operation of the turbinecombustion engine; wherein said processor is operative to determine thephysical condition and orientation of said one or more rotor blades bycomparing anticipated arrival times of one or more blades with actualarrival time information transmitted from said plurality of sensors andto analyze said information transmitted from said plurality of sensorsto identify and count the cycles in which each of said one or more rotorblades experiences resonant frequencies; wherein said memory isoperative to record the number of cycles and the frequencies andamplitudes of vibration for each resonant frequency; and wherein saidprocessor is operative to compare recent information with historicalinformation to develop a prediction based upon the frequencies and peakamplitudes of vibration of the number of cycles said one or more rotorblades may be expected to experience before failure and, using saidprediction, to schedule events relating to said turbine engine, saidevents including at least scheduled maintenance.
 13. The system of claim12 wherein said plurality of sensors includes eddy current sensors andproximity sensors.
 14. The system of claim 12 wherein said processor isfurther operative to determine an expected arrival time for differentparts of a blade whose physical condition and orientation are beingdetermined, and to compare said expected arrival times with actualarrival times for each of said parts of said blade.
 15. The system ofclaim 12 wherein said processor is further operative to analyze bladedamage to determine damage accumulation to one or more blades.
 16. Thesystem of claim 12 wherein said events include scheduling a shutdown ofsaid turbine engine prior to failure of said one or more blades.
 17. Thesystem of claim 14 wherein said sensors are positioned around thecircumference of said blades' path of rotation such that expected andactual arrival times for parts of each blade can be analyzed to identifydeformations in the shape of each blade and to determine the frequencyof vibration of each blade during the operation of said combustionturbine engine.
 18. The system of claim 15 wherein said processor isfurther operative to determine expected blade life by analyzing damageaccumulation for each cycle and to determine a predicted blade failureif said damage accumulation continues at the same rate.
 19. The systemof claim 17 wherein said processor is further operative to analyze saidfrequency of vibration to determine frequency trending for one or moreof said blades.
 20. The system of claim 18 wherein said memory isfurther operative to store information regarding damage to one or moreblades in a database and to make said information regarding damageaccessible for analyses to be performed in the future.